Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2362342
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory234.3 MiB
Average record size in memory104.0 B

Variable types

Text7
Categorical2
DateTime1
Numeric2

Alerts

review_id has unique valuesUnique

Reproduction

Analysis started2024-10-09 03:30:23.857322
Analysis finished2024-10-09 03:38:00.728191
Duration7 minutes and 36.87 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

review_id
Text

UNIQUE 

Distinct2362342
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:01.874195image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters51971524
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2362342 ?
Unique (%)100.0%

Sample

1st rowOQPeCnCIkeHIM_UI3oDFFQ
2nd rowcOc39ZC2AQGaGJyNfKRqPw
3rd rowQtzBWykt6W4bGl0MfjhAHQ
4th rowilodZfmS25rOMoX84nENBg
5th rowZd7fBocxfnD8ANd6dUEx8w
ValueCountFrequency (%)
ze4jw_3shatrug4dwezyxw 1
 
< 0.1%
c2sq-hldo-0yd03cxjjkow 1
 
< 0.1%
oqpecncikehim_ui3odffq 1
 
< 0.1%
coc39zc2aqgagjynfkrqpw 1
 
< 0.1%
qtzbwykt6w4bgl0mfjhahq 1
 
< 0.1%
ilodzfms25romox84nenbg 1
 
< 0.1%
d_f_an-xvfiq0o-9ezu3uw 1
 
< 0.1%
z1eog4jblqyqygw3gvgm4w 1
 
< 0.1%
cpn9iukhazjpxa69djg9vw 1
 
< 0.1%
cpo-mlpnko-k01vuhmauq 1
 
< 0.1%
Other values (2362332) 2362332
> 99.9%
2024-10-08T23:38:02.892882image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
g 1367593
 
2.6%
Q 1366408
 
2.6%
w 1365278
 
2.6%
A 1364404
 
2.6%
P 777245
 
1.5%
G 776604
 
1.5%
z 776604
 
1.5%
3 776588
 
1.5%
I 776443
 
1.5%
h 776293
 
1.5%
Other values (54) 41848064
80.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
g 1367593
 
2.6%
Q 1366408
 
2.6%
w 1365278
 
2.6%
A 1364404
 
2.6%
P 777245
 
1.5%
G 776604
 
1.5%
z 776604
 
1.5%
3 776588
 
1.5%
I 776443
 
1.5%
h 776293
 
1.5%
Other values (54) 41848064
80.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
g 1367593
 
2.6%
Q 1366408
 
2.6%
w 1365278
 
2.6%
A 1364404
 
2.6%
P 777245
 
1.5%
G 776604
 
1.5%
z 776604
 
1.5%
3 776588
 
1.5%
I 776443
 
1.5%
h 776293
 
1.5%
Other values (54) 41848064
80.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
g 1367593
 
2.6%
Q 1366408
 
2.6%
w 1365278
 
2.6%
A 1364404
 
2.6%
P 777245
 
1.5%
G 776604
 
1.5%
z 776604
 
1.5%
3 776588
 
1.5%
I 776443
 
1.5%
h 776293
 
1.5%
Other values (54) 41848064
80.5%
Distinct947202
Distinct (%)40.1%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:03.422943image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters51971524
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique606164 ?
Unique (%)25.7%

Sample

1st row5gRql5hu93bQegD9rPq6JQ
2nd rowPvujEckcOn9rrgUKUY14HQ
3rd rowErvhagcf9qKzTQ2nFao-zA
4th rowCq0j7hB0B3ebN7023BTXzw
5th row2LbWXy28Uik7qhUoWU_bdg
ValueCountFrequency (%)
bcwykql16ndpbdggh2kna 858
 
< 0.1%
g7zkl1wiwbbmd0kry_scw 657
 
< 0.1%
fr1hz2acab3oal3l6dykng 576
 
< 0.1%
1hm81n6n4ipifu5d2lokhw 538
 
< 0.1%
et8n-r7glwyqzhur6gcdnw 520
 
< 0.1%
byenop4buqepbjm1-bi3fa 513
 
< 0.1%
xw7zjagfr0wnvt6s_5kzfa 508
 
< 0.1%
vl12ehedt4owqgq0niqkzw 487
 
< 0.1%
ouodopbkf3aqfckuqenrdg 473
 
< 0.1%
pou3bbksiozfh50rxmnmew 457
 
< 0.1%
Other values (947192) 2356755
99.8%
2024-10-08T23:38:03.915474image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Q 1372094
 
2.6%
g 1367011
 
2.6%
w 1363460
 
2.6%
A 1363208
 
2.6%
I 786213
 
1.5%
u 782445
 
1.5%
f 782271
 
1.5%
n 781551
 
1.5%
T 781469
 
1.5%
W 781118
 
1.5%
Other values (54) 41810684
80.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Q 1372094
 
2.6%
g 1367011
 
2.6%
w 1363460
 
2.6%
A 1363208
 
2.6%
I 786213
 
1.5%
u 782445
 
1.5%
f 782271
 
1.5%
n 781551
 
1.5%
T 781469
 
1.5%
W 781118
 
1.5%
Other values (54) 41810684
80.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Q 1372094
 
2.6%
g 1367011
 
2.6%
w 1363460
 
2.6%
A 1363208
 
2.6%
I 786213
 
1.5%
u 782445
 
1.5%
f 782271
 
1.5%
n 781551
 
1.5%
T 781469
 
1.5%
W 781118
 
1.5%
Other values (54) 41810684
80.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Q 1372094
 
2.6%
g 1367011
 
2.6%
w 1363460
 
2.6%
A 1363208
 
2.6%
I 786213
 
1.5%
u 782445
 
1.5%
f 782271
 
1.5%
n 781551
 
1.5%
T 781469
 
1.5%
W 781118
 
1.5%
Other values (54) 41810684
80.4%
Distinct52166
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:04.053858image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters51971524
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique614 ?
Unique (%)< 0.1%

Sample

1st rowEsHSmxdLpBpU2bcN_V61zw
2nd row6_T2xzR74JqGCTPefAD8Tw
3rd rowjhvAqQfSJjqTo3SVBidcEw
4th row2KIDQyTh-HzLxOUEDqtDBg
5th rowntiIq1FNqduOyyowMFGh5A
ValueCountFrequency (%)
ab50qdwok0ddb6xorbitw 3808
 
0.2%
ac1aeyqs8z4_e2x5m3if2a 3714
 
0.2%
gxfmd0z4jevzbcsbpf4ctq 3069
 
0.1%
ytynqoub3hjkejfrj5tshw 2962
 
0.1%
isrtat9wngzb8jj2ykjuig 2693
 
0.1%
obnrlz4edhiscslbol8uaw 2646
 
0.1%
vqccl9pinl_wkgf-uf3fjg 2561
 
0.1%
c7qiqqc47aoev4pe3kong 2477
 
0.1%
gbtpc53zrg1zby3dt8mbcw 2332
 
0.1%
6a4gllfsgr-q6czxdlzbgq 2243
 
0.1%
Other values (52156) 2333837
98.8%
2024-10-08T23:38:04.241359image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Q 1361873
 
2.6%
g 1360122
 
2.6%
A 1354903
 
2.6%
w 1354710
 
2.6%
6 803136
 
1.5%
b 800801
 
1.5%
E 800014
 
1.5%
B 798532
 
1.5%
V 796701
 
1.5%
9 794944
 
1.5%
Other values (54) 41745788
80.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Q 1361873
 
2.6%
g 1360122
 
2.6%
A 1354903
 
2.6%
w 1354710
 
2.6%
6 803136
 
1.5%
b 800801
 
1.5%
E 800014
 
1.5%
B 798532
 
1.5%
V 796701
 
1.5%
9 794944
 
1.5%
Other values (54) 41745788
80.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Q 1361873
 
2.6%
g 1360122
 
2.6%
A 1354903
 
2.6%
w 1354710
 
2.6%
6 803136
 
1.5%
b 800801
 
1.5%
E 800014
 
1.5%
B 798532
 
1.5%
V 796701
 
1.5%
9 794944
 
1.5%
Other values (54) 41745788
80.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51971524
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Q 1361873
 
2.6%
g 1360122
 
2.6%
A 1354903
 
2.6%
w 1354710
 
2.6%
6 803136
 
1.5%
b 800801
 
1.5%
E 800014
 
1.5%
B 798532
 
1.5%
V 796701
 
1.5%
9 794944
 
1.5%
Other values (54) 41745788
80.3%

stars_x
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
5
1040199 
4
565065 
1
283587 
3
271236 
2
202255 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2362342
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row5
4th row5
5th row4

Common Values

ValueCountFrequency (%)
5 1040199
44.0%
4 565065
23.9%
1 283587
 
12.0%
3 271236
 
11.5%
2 202255
 
8.6%

Length

2024-10-08T23:38:04.303857image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-08T23:38:07.667186image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
5 1040199
44.0%
4 565065
23.9%
1 283587
 
12.0%
3 271236
 
11.5%
2 202255
 
8.6%

Most occurring characters

ValueCountFrequency (%)
5 1040199
44.0%
4 565065
23.9%
1 283587
 
12.0%
3 271236
 
11.5%
2 202255
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2362342
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 1040199
44.0%
4 565065
23.9%
1 283587
 
12.0%
3 271236
 
11.5%
2 202255
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2362342
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 1040199
44.0%
4 565065
23.9%
1 283587
 
12.0%
3 271236
 
11.5%
2 202255
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2362342
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 1040199
44.0%
4 565065
23.9%
1 283587
 
12.0%
3 271236
 
11.5%
2 202255
 
8.6%

text
Text

Distinct2359595
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:08.456259image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length5000
Median length4671
Mean length544.57616
Min length1

Characters and Unicode

Total characters1286475131
Distinct characters2428
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2356919 ?
Unique (%)99.8%

Sample

1st rowOrdered two combo dinner plates for my two little kids and Cali rolls for us to start with. I have to admit that was the worst combo ever, beef teriyaki tasted like pot roast and was very tough , it came with steamed vegetables instead of tempura , and carrots on the plate were dry and looked bad, kids ended up eating rice only, I don't mind paying $20 for a good bento box, but this was honestly terrible, so $40 for two bowls of rice for the children. Our Cali rolls were good but we didn't want to try anything else based on the disappointing experience with kids dinners. My cup of hot green tea arrived barely warm. It was out first time here, $60 bill and , and yes, deep fried bananas soaked in tons of honey for free, they were very friendly but just that will not bring us back.
2nd rowI thought Morimoto was just ok. Seafood was fresh. The service was very good as well as the ambience. It would of been nice to have a menu of specialty rolls just to have more variety from the mundane traditional rolls. So what I decided to do was order yellowtail jalapeño from the cold appetizer menu which was pretty good, and placed it on top of my shrimp tempura roll. I just think for someone who is an "iron chef", I expected more. I believe would go back but before going back to Morimoto I would like to try other Japanese restaurants first.
3rd rowVery clean kitchen. More so than most restaurants. Quality food at a fair price. Love their crab ragoons.
4th rowThis is a delicious market with fresh food and made to order food!! Bakery selection, deli meats and cheese, it's all amazing!!! Pizzas ready to throw in the oven and wines ready to pair!!! Deliciousness around every corner in this big Italian market!!
5th rowSmall bite: Satisfying noodle soup, splendid for those cold winter days. Came here on the trip to visit the brother. I had the house special noodle soup with beef, greens, cabbage, and hand drawn noodle. I've actually been to Lanzhou, the capital of Gansu province in China, and had the beef lamian (hand-pulled noodle), which is a specialty of that area. But the last time that I was in Lanzhou was 2009, so it's hard to compare. What I can tell you is that the noodle soup was hearty and tasty. The hand-pulled noodles have a distinctive chewiness, which melds well with the chunks of beef. I can definitely see myself coming here on a frigid February day. The decor is functional. I appreciate the number cards next to each table, for the waitstaff to know which table to attend. Other restaurants might keep this information behind the scenes, but this shop skips on such pretensions. Soundtrack: Autotuned Chinese pop.
ValueCountFrequency (%)
the 12565730
 
5.3%
and 8538339
 
3.6%
a 6089419
 
2.6%
i 5683217
 
2.4%
to 5152933
 
2.2%
was 4796312
 
2.0%
of 3418938
 
1.4%
it 3116006
 
1.3%
is 2908194
 
1.2%
for 2778734
 
1.2%
Other values (864860) 181698341
76.7%
2024-10-08T23:38:09.187899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
236723090
18.4%
e 126848949
 
9.9%
t 86928548
 
6.8%
a 84060653
 
6.5%
o 73535653
 
5.7%
i 62104778
 
4.8%
s 60709826
 
4.7%
n 59498378
 
4.6%
r 58355701
 
4.5%
h 49096962
 
3.8%
Other values (2418) 388612593
30.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1286475131
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
236723090
18.4%
e 126848949
 
9.9%
t 86928548
 
6.8%
a 84060653
 
6.5%
o 73535653
 
5.7%
i 62104778
 
4.8%
s 60709826
 
4.7%
n 59498378
 
4.6%
r 58355701
 
4.5%
h 49096962
 
3.8%
Other values (2418) 388612593
30.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1286475131
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
236723090
18.4%
e 126848949
 
9.9%
t 86928548
 
6.8%
a 84060653
 
6.5%
o 73535653
 
5.7%
i 62104778
 
4.8%
s 60709826
 
4.7%
n 59498378
 
4.6%
r 58355701
 
4.5%
h 49096962
 
3.8%
Other values (2418) 388612593
30.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1286475131
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
236723090
18.4%
e 126848949
 
9.9%
t 86928548
 
6.8%
a 84060653
 
6.5%
o 73535653
 
5.7%
i 62104778
 
4.8%
s 60709826
 
4.7%
n 59498378
 
4.6%
r 58355701
 
4.5%
h 49096962
 
3.8%
Other values (2418) 388612593
30.2%

date
Date

Distinct2350003
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
Minimum2005-02-16 04:06:26
Maximum2022-01-19 19:48:25
2024-10-08T23:38:09.266319image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-08T23:38:09.349866image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

name
Text

Distinct36664
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:09.575728image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length17.627972
Min length2

Characters and Unicode

Total characters41643299
Distinct characters137
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique404 ?
Unique (%)< 0.1%

Sample

1st rowUmai Japanese Restaurant
2nd rowMorimoto
3rd rowEgg Roll King
4th rowMazzaro's Italian Market
5th rowNan Zhou Hand Drawn Noodle House
ValueCountFrequency (%)
365158
 
5.3%
restaurant 197082
 
2.9%
the 174859
 
2.6%
cafe 138659
 
2.0%
bar 126543
 
1.8%
grill 124899
 
1.8%
pizza 98704
 
1.4%
house 86084
 
1.3%
and 63199
 
0.9%
kitchen 53684
 
0.8%
Other values (19851) 5414117
79.1%
2024-10-08T23:38:09.892587image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4486806
 
10.8%
a 3766157
 
9.0%
e 3600432
 
8.6%
i 2409535
 
5.8%
r 2338512
 
5.6%
o 2193556
 
5.3%
s 2094290
 
5.0%
n 2093731
 
5.0%
t 1819347
 
4.4%
l 1527979
 
3.7%
Other values (127) 15312954
36.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41643299
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4486806
 
10.8%
a 3766157
 
9.0%
e 3600432
 
8.6%
i 2409535
 
5.8%
r 2338512
 
5.6%
o 2193556
 
5.3%
s 2094290
 
5.0%
n 2093731
 
5.0%
t 1819347
 
4.4%
l 1527979
 
3.7%
Other values (127) 15312954
36.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41643299
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4486806
 
10.8%
a 3766157
 
9.0%
e 3600432
 
8.6%
i 2409535
 
5.8%
r 2338512
 
5.6%
o 2193556
 
5.3%
s 2094290
 
5.0%
n 2093731
 
5.0%
t 1819347
 
4.4%
l 1527979
 
3.7%
Other values (127) 15312954
36.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41643299
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4486806
 
10.8%
a 3766157
 
9.0%
e 3600432
 
8.6%
i 2409535
 
5.8%
r 2338512
 
5.6%
o 2193556
 
5.3%
s 2094290
 
5.0%
n 2093731
 
5.0%
t 1819347
 
4.4%
l 1527979
 
3.7%
Other values (127) 15312954
36.8%

city
Text

Distinct918
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:10.096456image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length52
Median length25
Mean length9.6298868
Min length4

Characters and Unicode

Total characters22749086
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowLansdale
2nd rowPhiladelphia
3rd rowIndianapolis
4th rowSaint Petersburg
5th rowPhiladelphia
ValueCountFrequency (%)
philadelphia 343943
 
10.9%
new 250896
 
8.0%
orleans 238422
 
7.6%
nashville 163223
 
5.2%
tampa 153262
 
4.9%
indianapolis 125178
 
4.0%
tucson 124978
 
4.0%
louis 122004
 
3.9%
saint 121314
 
3.9%
reno 100426
 
3.2%
Other values (788) 1397633
44.5%
2024-10-08T23:38:10.363568image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2765907
 
12.2%
e 2063425
 
9.1%
l 1897234
 
8.3%
i 1851789
 
8.1%
n 1526715
 
6.7%
s 1158813
 
5.1%
r 1136808
 
5.0%
o 1047972
 
4.6%
h 1024797
 
4.5%
779374
 
3.4%
Other values (49) 7496252
33.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 22749086
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2765907
 
12.2%
e 2063425
 
9.1%
l 1897234
 
8.3%
i 1851789
 
8.1%
n 1526715
 
6.7%
s 1158813
 
5.1%
r 1136808
 
5.0%
o 1047972
 
4.6%
h 1024797
 
4.5%
779374
 
3.4%
Other values (49) 7496252
33.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 22749086
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2765907
 
12.2%
e 2063425
 
9.1%
l 1897234
 
8.3%
i 1851789
 
8.1%
n 1526715
 
6.7%
s 1158813
 
5.1%
r 1136808
 
5.0%
o 1047972
 
4.6%
h 1024797
 
4.5%
779374
 
3.4%
Other values (49) 7496252
33.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 22749086
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2765907
 
12.2%
e 2063425
 
9.1%
l 1897234
 
8.3%
i 1851789
 
8.1%
n 1526715
 
6.7%
s 1158813
 
5.1%
r 1136808
 
5.0%
o 1047972
 
4.6%
h 1024797
 
4.5%
779374
 
3.4%
Other values (49) 7496252
33.0%

state
Categorical

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
PA
549293 
FL
396668 
LA
279631 
TN
217668 
MO
176774 
Other values (14)
742308 

Length

Max length3
Median length2
Mean length2.0000017
Min length2

Characters and Unicode

Total characters4724688
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPA
2nd rowPA
3rd rowIN
4th rowFL
5th rowPA

Common Values

ValueCountFrequency (%)
PA 549293
23.3%
FL 396668
16.8%
LA 279631
11.8%
TN 217668
 
9.2%
MO 176774
 
7.5%
IN 167784
 
7.1%
AZ 133441
 
5.6%
NV 122108
 
5.2%
CA 105966
 
4.5%
NJ 85544
 
3.6%
Other values (9) 127465
 
5.4%

Length

2024-10-08T23:38:10.453719image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pa 549293
23.3%
fl 396668
16.8%
la 279631
11.8%
tn 217668
 
9.2%
mo 176774
 
7.5%
in 167784
 
7.1%
az 133441
 
5.6%
nv 122108
 
5.2%
ca 105966
 
4.5%
nj 85544
 
3.6%
Other values (9) 127465
 
5.4%

Most occurring characters

ValueCountFrequency (%)
A 1102700
23.3%
L 694813
14.7%
N 593121
12.6%
P 549293
11.6%
F 396668
 
8.4%
I 236421
 
5.0%
T 217671
 
4.6%
M 176781
 
3.7%
O 176780
 
3.7%
Z 133441
 
2.8%
Other values (9) 446999
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4724688
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1102700
23.3%
L 694813
14.7%
N 593121
12.6%
P 549293
11.6%
F 396668
 
8.4%
I 236421
 
5.0%
T 217671
 
4.6%
M 176781
 
3.7%
O 176780
 
3.7%
Z 133441
 
2.8%
Other values (9) 446999
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4724688
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1102700
23.3%
L 694813
14.7%
N 593121
12.6%
P 549293
11.6%
F 396668
 
8.4%
I 236421
 
5.0%
T 217671
 
4.6%
M 176781
 
3.7%
O 176780
 
3.7%
Z 133441
 
2.8%
Other values (9) 446999
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4724688
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1102700
23.3%
L 694813
14.7%
N 593121
12.6%
P 549293
11.6%
F 396668
 
8.4%
I 236421
 
5.0%
T 217671
 
4.6%
M 176781
 
3.7%
O 176780
 
3.7%
Z 133441
 
2.8%
Other values (9) 446999
9.5%

stars_y
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7926238
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:10.502026image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q13.5
median4
Q34
95-th percentile4.5
Maximum5
Range4
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.62617943
Coefficient of variation (CV)0.16510454
Kurtosis1.4029231
Mean3.7926238
Median Absolute Deviation (MAD)0.5
Skewness-1.0416825
Sum8959474.5
Variance0.39210067
MonotonicityNot monotonic
2024-10-08T23:38:10.549013image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 917530
38.8%
3.5 529301
22.4%
4.5 506745
21.5%
3 220536
 
9.3%
2.5 100453
 
4.3%
2 41273
 
1.7%
5 26378
 
1.1%
1.5 18292
 
0.8%
1 1834
 
0.1%
ValueCountFrequency (%)
1 1834
 
0.1%
1.5 18292
 
0.8%
2 41273
 
1.7%
2.5 100453
 
4.3%
3 220536
 
9.3%
3.5 529301
22.4%
4 917530
38.8%
4.5 506745
21.5%
5 26378
 
1.1%
ValueCountFrequency (%)
5 26378
 
1.1%
4.5 506745
21.5%
4 917530
38.8%
3.5 529301
22.4%
3 220536
 
9.3%
2.5 100453
 
4.3%
2 41273
 
1.7%
1.5 18292
 
0.8%
1 1834
 
0.1%

review_count
Real number (ℝ)

Distinct1132
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean493.02809
Minimum5
Maximum7568
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:10.627565image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile22
Q190
median221
Q3508
95-th percentile1984
Maximum7568
Range7563
Interquartile range (IQR)418

Descriptive statistics

Standard deviation850.75949
Coefficient of variation (CV)1.7255802
Kurtosis23.833053
Mean493.02809
Median Absolute Deviation (MAD)160
Skewness4.3194681
Sum1.164701 × 109
Variance723791.71
MonotonicityNot monotonic
2024-10-08T23:38:10.690417image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 8179
 
0.3%
41 8103
 
0.3%
54 8020
 
0.3%
19 7833
 
0.3%
29 7821
 
0.3%
38 7814
 
0.3%
24 7782
 
0.3%
25 7756
 
0.3%
46 7717
 
0.3%
32 7625
 
0.3%
Other values (1122) 2283692
96.7%
ValueCountFrequency (%)
5 5530
0.2%
6 5550
0.2%
7 6069
0.3%
8 6070
0.3%
9 6516
0.3%
10 6752
0.3%
11 6694
0.3%
12 7142
0.3%
13 7099
0.3%
14 7264
0.3%
ValueCountFrequency (%)
7568 3808
0.2%
7400 3714
0.2%
6093 3069
0.1%
5721 2962
0.1%
5193 2646
0.1%
5185 2693
0.1%
5070 2561
0.1%
4876 2477
0.1%
4554 2332
0.1%
4421 2243
0.1%
Distinct31643
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size36.0 MiB
2024-10-08T23:38:10.901510image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length503
Median length223
Mean length65.453834
Min length11

Characters and Unicode

Total characters154624341
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291 ?
Unique (%)< 0.1%

Sample

1st rowSushi Bars, Japanese, Restaurants
2nd rowJapanese, American (Traditional), American (New), Restaurants, Sushi Bars, Asian Fusion
3rd rowChinese, Restaurants, Food, Specialty Food
4th rowSpecialty Food, Delis, Coffee Roasteries, Butcher, Meat Shops, Food, Restaurants, Grocery, Italian
5th rowSpecialty Food, Noodles, Ethnic Food, Chinese, Comfort Food, Restaurants, Food
ValueCountFrequency (%)
restaurants 2364302
 
12.7%
bars 1214768
 
6.5%
1207058
 
6.5%
food 1137791
 
6.1%
american 1042266
 
5.6%
nightlife 686060
 
3.7%
traditional 505721
 
2.7%
new 505431
 
2.7%
breakfast 435765
 
2.3%
brunch 433642
 
2.3%
Other values (830) 9097358
48.8%
2024-10-08T23:38:11.172731image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16267820
 
10.5%
a 14685389
 
9.5%
e 13370475
 
8.6%
s 10983002
 
7.1%
, 10683827
 
6.9%
r 9475019
 
6.1%
t 9325064
 
6.0%
n 8754649
 
5.7%
i 7693411
 
5.0%
o 5620123
 
3.6%
Other values (48) 47765562
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 154624341
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
16267820
 
10.5%
a 14685389
 
9.5%
e 13370475
 
8.6%
s 10983002
 
7.1%
, 10683827
 
6.9%
r 9475019
 
6.1%
t 9325064
 
6.0%
n 8754649
 
5.7%
i 7693411
 
5.0%
o 5620123
 
3.6%
Other values (48) 47765562
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 154624341
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
16267820
 
10.5%
a 14685389
 
9.5%
e 13370475
 
8.6%
s 10983002
 
7.1%
, 10683827
 
6.9%
r 9475019
 
6.1%
t 9325064
 
6.0%
n 8754649
 
5.7%
i 7693411
 
5.0%
o 5620123
 
3.6%
Other values (48) 47765562
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 154624341
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
16267820
 
10.5%
a 14685389
 
9.5%
e 13370475
 
8.6%
s 10983002
 
7.1%
, 10683827
 
6.9%
r 9475019
 
6.1%
t 9325064
 
6.0%
n 8754649
 
5.7%
i 7693411
 
5.0%
o 5620123
 
3.6%
Other values (48) 47765562
30.9%

Interactions

2024-10-08T23:37:46.521431image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-08T23:37:45.807746image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-08T23:37:46.865857image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-08T23:37:46.167233image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-10-08T23:38:11.247175image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
review_countstars_xstars_ystate
review_count1.0000.0450.2920.137
stars_x0.0451.0000.2310.041
stars_y0.2920.2311.0000.056
state0.1370.0410.0561.000

Missing values

2024-10-08T23:37:47.739197image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-08T23:37:49.487062image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

review_iduser_idbusiness_idstars_xtextdatenamecitystatestars_yreview_countcategories
2459551OQPeCnCIkeHIM_UI3oDFFQ5gRql5hu93bQegD9rPq6JQEsHSmxdLpBpU2bcN_V61zw2Ordered two combo dinner plates for my two little kids and Cali rolls for us to start with. I have to admit that was the worst combo ever, beef teriyaki tasted like pot roast and was very tough , it came with steamed vegetables instead of tempura , and carrots on the plate were dry and looked bad, kids ended up eating rice only, I don't mind paying $20 for a good bento box, but this was honestly terrible, so $40 for two bowls of rice for the children. Our Cali rolls were good but we didn't want to try anything else based on the disappointing experience with kids dinners. My cup of hot green tea arrived barely warm. It was out first time here, $60 bill and , and yes, deep fried bananas soaked in tons of honey for free, they were very friendly but just that will not bring us back.2012-08-25 01:39:53Umai Japanese RestaurantLansdalePA4.5219Sushi Bars, Japanese, Restaurants
2519170cOc39ZC2AQGaGJyNfKRqPwPvujEckcOn9rrgUKUY14HQ6_T2xzR74JqGCTPefAD8Tw3I thought Morimoto was just ok. Seafood was fresh. The service was very good as well as the ambience. It would of been nice to have a menu of specialty rolls just to have more variety from the mundane traditional rolls. So what I decided to do was order yellowtail jalapeño from the cold appetizer menu which was pretty good, and placed it on top of my shrimp tempura roll. I just think for someone who is an "iron chef", I expected more. I believe would go back but before going back to Morimoto I would like to try other Japanese restaurants first.2017-06-03 18:48:15MorimotoPhiladelphiaPA4.51914Japanese, American (Traditional), American (New), Restaurants, Sushi Bars, Asian Fusion
2979996QtzBWykt6W4bGl0MfjhAHQErvhagcf9qKzTQ2nFao-zAjhvAqQfSJjqTo3SVBidcEw5Very clean kitchen. More so than most restaurants. Quality food at a fair price. Love their crab ragoons.2018-05-02 23:20:05Egg Roll KingIndianapolisIN3.517Chinese, Restaurants, Food, Specialty Food
193893ilodZfmS25rOMoX84nENBgCq0j7hB0B3ebN7023BTXzw2KIDQyTh-HzLxOUEDqtDBg5This is a delicious market with fresh food and made to order food!! Bakery selection, deli meats and cheese, it's all amazing!!! Pizzas ready to throw in the oven and wines ready to pair!!! Deliciousness around every corner in this big Italian market!!2018-06-04 18:20:46Mazzaro's Italian MarketSaint PetersburgFL4.51551Specialty Food, Delis, Coffee Roasteries, Butcher, Meat Shops, Food, Restaurants, Grocery, Italian
3622658Zd7fBocxfnD8ANd6dUEx8w2LbWXy28Uik7qhUoWU_bdgntiIq1FNqduOyyowMFGh5A4Small bite: Satisfying noodle soup, splendid for those cold winter days.\n\nCame here on the trip to visit the brother. I had the house special noodle soup with beef, greens, cabbage, and hand drawn noodle.\n\nI've actually been to Lanzhou, the capital of Gansu province in China, and had the beef lamian (hand-pulled noodle), which is a specialty of that area. But the last time that I was in Lanzhou was 2009, so it's hard to compare.\n\nWhat I can tell you is that the noodle soup was hearty and tasty. The hand-pulled noodles have a distinctive chewiness, which melds well with the chunks of beef. I can definitely see myself coming here on a frigid February day.\n\nThe decor is functional. I appreciate the number cards next to each table, for the waitstaff to know which table to attend. Other restaurants might keep this information behind the scenes, but this shop skips on such pretensions.\n\nSoundtrack: Autotuned Chinese pop.2017-05-20 05:38:33Nan Zhou Hand Drawn Noodle HousePhiladelphiaPA4.02188Specialty Food, Noodles, Ethnic Food, Chinese, Comfort Food, Restaurants, Food
490496JIzjJ5UWYkYvwC6VvCJM5A_L8hgWYS4Ma0PCswu99CfQL8rhRyXtpq2nCE0il1KN_g1I ordered a hot chocolate and it tasted like hot water sprinkled with coco powder. I don't know how you mess up powder hot chocolate! I had 1 sip and threw it away2015-05-12 19:25:36Coral Tree CafeSanta BarbaraCA3.028Cafes, Burgers, Sandwiches, Restaurants
4445201ZE4JW_3shaTrug4dweZyxw_R8QOI97rsk_P9gZQFkcZgjGIRx6Ium6U69owDUB4phQ5Delicious!!!! Love the traditional Bahn Mi. Got them to go and had the veggie on the side so the bread stays crispy. The sandwich was wrapped in wax paper (similar to your kitchen's wax paper) except this was printed to look like newspaper. No ink came off when I wetted the wax paper. The light bulb tea is a nice gimmick (you get to keep it as a souvenir) and when I got them to go, there's a seal on top which kept the liquid from spilling. Will be back to try other flavors (Bahn Mi & tea) and will be asking for the loyalty card.2017-07-14 22:48:39Tu's Tea & Banh Mi South PhillyPhiladelphiaPA4.071Restaurants, Bubble Tea, Bakeries, Food, Noodles, Sandwiches, Vietnamese
4256387ETUO6lAeVh7KyMkBNzT5tghopT7mTV-o_JtcLmr2fITQV0SHmvYtXqdv8-AsqshV6w4Great spot for getting together with friends. We had the Betty Burger, spicy chicken sandwich and the Cobb salad. We finished with the chocolate cake for dessert. Everything was delicious . They also have a good selection of beers.2018-02-11 03:37:25Smokin BettysPhiladelphiaPA3.5796Nightlife, Bars, American (New), Barbeque, Restaurants
3398691aBuXfj6tmqfDIIf25Oz6sAOST0JZEIsWWvgjYBS1jP_w2D-8pjS2NB9ut8AIUFEu2w4This is a fun night out and I highly recommend it if you have your expectations in check. There are various reviews on here slamming the food and service. If you are wondering if it can be that bad. Yep, it is. Tasteless burgers, lumpy; lukewarm queso sauce, times of intense thirst because your order just never comes, you get the gist. The food is on par with "gas station gourmet". If you're wondering how they can find you once the theater goes dark well...they can't. No less than four times. we were approached read: interrupted by red (maroon?) shirts trying to find who ordered the barbecue wings, margarita, etc.-we had not. But yet they never found us to deliver our popcorn and beverages. The waitstaff (white shirts) answer the buzzers and take your orders, the red shirts are apparently the runners. The red shirt team needs some work-or at least they are a convenient scapegoat for the white shirts. \n\nSo again, dial down your expectations, eat before you go and enjoy this for what it is, a really comfy theater that serves booze and stick to the dessert, appetizers or popcorn. Oh and arrive at least 30 minutes early as recommended, your hopes of getting decent service go down exponentially after the movie starts. I'm not sure why management doesn't improve the food/service, they could really have a winner.2015-03-22 13:07:30Movie Tavern CollegevilleCollegevillePA3.5430Cinema, Fast Food, Restaurants, Arts & Entertainment, American (New)
1855631Tn0xCepAcU6KG0WzeZ3f0AgeFBBS--O8vg_tPhSSKlywirRj3rHVakROLZRSTH8MTQ1Wow 2hrs waiting for delivery food still not here. Dont order a delivery on a friday night. We have been regular customers for a long time . Very dissapointed.2015-02-07 01:35:53Ocean Asian CuisineSewellNJ3.578Thai, Restaurants, Asian Fusion, Japanese
review_iduser_idbusiness_idstars_xtextdatenamecitystatestars_yreview_countcategories
1369723VMfG9vLTzopd261mi1xb8QJ7MC2wPN5IX2HXODhtGN9AVQcCL9PiNL_wkGf-uF3fjg5Food was wonderful. Fried shrimp platter on a bed of fries & hush puppies were hot & crispy with a ton of flavor. Shrimp pasta with red sauce had soooo much flavor. We wanted to slurp the leftover sauce right out of bowl. Cajun red bean & rice with added buttermilk fried chicken breast strips was a perfect melody of flavor. It had a hint of spice from sausage but not too much. The staff was AMAZING. Very friendly, there when you needed them. The best part was the manager. He was awesome!! Very friendly, went out of way to explain to my son what a hush puppy was. He gave great advice on places to go while in New Orleans. He accidentally gave us a wrong dish. We had no idea, we think it was probably better then what we originally ordered & he still took it of the bill. The manager treated us like he owned the restaurant, so devoted, true to his career & love for food. I recommend you check in early for balcony seating. If there is a long wait, you could window shop close to restaurant. With Covid, the French Corridors are pretty empty, but balcony was an hour wait. Balcony will give you the real feel of how quaint & beautiful the French quarters are.2020-07-28 15:52:25Royal HouseNew OrleansLA4.05070American (New), Restaurants, Sandwiches, Seafood, Cajun/Creole
3352036Z-Lk6CPpQekHKc46XvXalAVtuEzOt1dzY9AM4lcih7ZgZhA88ILcgEP9DNwZDx7f0A4This place was so much fun! I had never been to a place like it before. Although it was crazy crowded on a Saturday night, it had an awesome vibe with different live bands on every floor. Definitely a place I would love to go to again next time I'm in Nashville.2013-10-28 03:12:27Honky Tonk CentralNashvilleTN3.5647Hotels & Travel, Pubs, Bars, Nightlife, Restaurants, American (Traditional), Music Venues, Southern, Arts & Entertainment, Chicken Wings
4133886LLPVwLZcUOmpEVBwEMsCtQpJWK3udsDI4K1MIAPgNfcgaFLM_Vow8OMcMK3NJWJ8pQ3Didn't receive biscuits with bucket meal. And they shorted me 3 chocolate chip cookies.2020-11-05 22:47:33KFCPhiladelphiaPA2.016Chicken Wings, Restaurants, Fast Food, Chicken Shop
3640819d3rR8SxiKcR7R7M-rY4KvQWaX5rCOD6UFIPHALwugTHw4Do_B7sfhfsn4TQV1h0psg4The food I had was on-par with other quality restaurants in the area. Philadelphia Chinatown is starting to lose many of its authentic food places, so it's nice to see a place like this come up where they have exquisite décor and a VIP style karaoke lounge, with several other rooms. The pricing is a bit higher than other places. You are basically paying extra for the ambiance and the excellent English translations in the menu so that you know what you are getting. \n\nIt gets 4 stars instead of 5 mainly because of price, but also because the food didn't wow me. I would still go back though!\n\nThe review about the water glasses being "too small", if you want more water, they will give you more water. A lot of people tend to waste water in bigger glasses anyway, and sometimes places pour you more water even if you ask them not to! So why the big fuss over smaller glasses? I think the amount is still reasonable even though maybe not plentiful, but it's not like that's all you get for water either.2016-08-01 14:01:18Canton 11PhiladelphiaPA3.5100Restaurants, Food, Dim Sum, Cantonese, Szechuan, Bars, Cocktail Bars, Nightlife, Karaoke, Food Delivery Services, Chinese, Sushi Bars
3628410D0hfpc9tA-9PIW34bTXJEwbkwbO0SvQzVAgrT_zH3MOAzcPCPkaTp46iJxwMv0LjVw5Yep. Gave it five stars. The experience from the start was excellent. So many good choices to pick from on the menu means everyone will find something they like. Even with the side dishes you get to ample choices. The food was delish. It wasn't dry. The flavor so good I didn't think you even needed bbq sauce. The guys at the counter we friendly. You can tell they are working hard and are putting together a great meal. Went here on a whim since I am from out of town and I can honestly say since I've been in Reno this is hands down the best food I've had. Thanks guys. You nailed it!2019-06-29 19:29:16Butcher's Kitchen CHAR-B-QUERenoNV4.5543Gastropubs, Bars, Burgers, Salad, Restaurants, Sandwiches, Wine Bars, Nightlife, Barbeque
3197179_v5la5Z7NQQn6XfuPSQAFAYEkIueEvWjQU4FG3e0g99gE7ERTbnPXmdh4sGrHg5LRQ2Every time we order through DoorDash our order is missing the ranch. This is at least the third time it has happened. Since you are not face to face with the customer, and the customer has no way to double check the bag, you would hope that the order is correct when you send it out the door.2020-12-29 19:25:13WingstopRenoNV3.016Restaurants, Chicken Wings
2615868s0O_yiDCEiLlufoHrxjmFA6TAa3ViO9EcAznbWza0aPwRtsxLNG5ta65Gatr09cnPg5I can update my review now that we've been for dinner. OMG this place is absolutely amazing. The food is fantastic and the service is great! The menu choices are numerous so I will undoubtedly be going back to try other things! \n\nWhat we got:\nWe started with the french pate. Duck and Pork. Served with a small salad, cornichons, dijon mustard and fresh baguette. Delicious! The table near us got the traditional Alsatian flatbread, which I'm definitely getting the next time.\n\nMains:\nI got the chicken mustard and my husband got the steak au puoive. Both we delicious. Again, we were sitting near the kitchen so saw some amazing dishes go out. They have a dish resembling a chicken schnitzel and the Osso Bucco looked divine! And the savory crepes? Like I said, we are definitely going back!\n\nThey have a few choices of wine - by the bottle or by the glass. They are very reasonably prices and very good! Dessert we went with chocolate mousse to finish the wine with. One of the best mousses I've had in a long time.\n\nAgain, we are keeping this on our go to list and are looking forward to going back!2018-07-12 15:00:21Alsace french bistroTierra VerdeFL4.5113French, Brasseries, Food, Restaurants, Coffee & Tea, Diners, Breakfast & Brunch
1955222EgSdGKHdun5EQ8R6c4CxoAHH2BKGc0LJNXaQnAEt7JewQtUn-vphzwt_cOQVkDlyow5Tried this place based on a friends recommendation. Great Food, good portions, and reasonable prices. As everyone mentions, you would not expect such a nice restaurant in the middle of this little dingy strip mall in Deptford. Very nice inside, casual but nicely decorated. Food is the best Tai food we have found in South Jersey. No need to go the Philly for good Tai Cuisine. Menu has photos of the dishes and the presentation of each dish is wonderful. New Favorite restaurant. Do not know how anyone could give this restaurant a bad review unless they are the competition and are trying to scare people away!!! Try this place, you won't be disappointed.2018-09-05 21:08:33Pinto Thong Thai CuisineDeptfordNJ4.5131Thai, Salad, Gluten-Free, Restaurants, Noodles
227652NpnPNok9VlQFuwEiLhP_lAxfWfe8_0aTnbkr_w1E55dg7hsCR9k_GND2QoQyVkITBg4Nice place to chilling with family. The food is great, but the service is not that friendly.2019-12-22 00:36:29Pho VoorheesVoorheesNJ4.5132Bubble Tea, Soup, Restaurants, Vietnamese, Food
4091691C2sq-HlDO-0YD03cXjJKOw7sxG7coheaKqmAvE0unzvAxV-GAlJLV-vNUpUGSkg77Q1I ordered a sandwich, half salad, and half soup. They stuffed it all in this bag that was obviously too small. I quickly checked everything to ensure that it was all and noticed I didn't have chips. I told the lady behind the counter and she kept swearing that they were in the bottom of the bag- which they weren't. Also, I paid for extra apple chips in my salad and received a smaller than normal portion.2019-06-19 19:39:23Panera BreadJenkintownPA2.585Sandwiches, Restaurants, Soup, Breakfast & Brunch, Bagels, Food, Salad, Bakeries, American (New)